{"id":"W2472302001","doi":"10.1007/978-3-319-27702-8_9","title":"Online Loop-Closure Detection via Dynamic Sparse Representation","year":2016,"lang":"en","type":"book-chapter","venue":"Springer tracts in advanced robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Sparse approximation; Simultaneous localization and mapping; Closure (psychology); Representation (politics); Loop (graph theory); Matching (statistics); Artificial intelligence; Scalability; Minification; Algorithm; Computer vision; Robot; Mathematics; Mobile robot","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009533848,0.0005516608,0.000533363,0.0004281877,0.00005963517,0.00003735766,0.0001903883,0.0006071401,0.00004765372],"category_scores_gemma":[0.00005230016,0.0005727898,0.0001515637,0.0001157608,0.00006169643,0.0002414109,0.00003719541,0.000729229,0.0000966635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005382577,"about_ca_system_score_gemma":0.00002874514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003387482,"about_ca_topic_score_gemma":0.0003453581,"domain_scores_codex":[0.9978839,0.000018285,0.0007628373,0.0005354967,0.0003719423,0.0004274987],"domain_scores_gemma":[0.9988042,0.0001030959,0.0002186554,0.0006185737,0.0001286732,0.0001268423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002388603,0.00004039401,0.00004029352,0.000134314,0.00004839187,0.00005618922,0.00002309691,0.9301776,0.004552073,0.001952891,0.00000489034,0.06294597],"study_design_scores_gemma":[0.002496207,0.0001965473,0.002603108,0.00202941,0.0002528645,0.00004959276,0.00002359618,0.9555982,0.004560128,0.02064809,0.009019675,0.002522556],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002578662,0.0009654889,0.9645098,0.0001048175,0.003200549,0.0008171432,0.00006146872,0.0006620332,0.02709998],"genre_scores_gemma":[0.8147002,0.008725375,0.06365894,0.0001496193,0.001089533,0.00003568292,0.0007204596,0.001284741,0.1096354],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9008509,"threshold_uncertainty_score":0.9996724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01359356395772906,"score_gpt":0.2378018821491533,"score_spread":0.2242083181914242,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}